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Using neural networks to evaluate neural networks

Functional MRI studies aided by neural net analysis has been used to test a …

When this story hit the popular press, there were hyperbolic headlines referring to "mental time travel" and the ability to predict what someone will be thinking about. The actual research article is, not surprisingly, a bit less glamorous. The phrase "mental time travel" refers to a model of memory recall in which the areas of the brain that were activated during the mental processing an event are re-activated during its recall. In a sense, it was proposed that, to remember an event, parts of your brain re-live it. The results of these experiments, which used functional MRI imaging, suggest that this is an accurate model of the brain's actions during recall.

The mind reading aspect comes from the use of three categories of pictures—faces, locations, and objects—in the recall tests. As part of the recall process, areas of the brain corresponding to each of these was activated seconds in advance of the actual recall, indicating that a rough idea of the task being processed could be identified based on brain scans alone.

One thing that leapt out at me from reading the paper was the way the analysis was performed. For each individual in the study, a neural network was trained on both background brain activity and during specific recall tasks. The network was then used to classify which task was happening, resulting in the accurate correlations described above. It's interesting to think of a computer program based on a brain model being used to evaluate abrain.

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